Get More from Your VFDs with Predictive Maintenance

Get More from VFDs with Predictive Maintenance

Variable-frequency drives run integral production operations, and predictive maintenance can help avoid unplanned downtime and unneeded replacements.

By Andy Gagnon, product manager, Rockwell Automation

If you’re like many car owners, you take your car in for regular oil changes but struggle to keep up with the manufacturer’s recommended service schedule. You might also wonder if an oil change is required based on how you drive your car.

Thanks to the diagnostic capabilities of cars entering the marketplace, we now can do away with much of the guesswork that comes with servicing our vehicles. Data is collected on critical vehicle components and used to alert us of impending issues. This can help maintain our cars based on actual needs versus industry averages and do so before a costly and inconvenient breakdown occurs.

This is predictive maintenance, and it holds similar potential for maintaining your industrial operation. To understand its true impact, though, it’s important to first understand the difference between preventive and predictive maintenance.

Preventive vs. Predictive Maintenance

Preventive maintenance involves building a maintenance schedule to service or replace devices based on their expected life spans. This certainly is better than a run-to-fail maintenance approach, which makes unscheduled downtime a routine and costly part of your operations.

Still, proactive maintenance is conducted based on a set schedule rather than a device’s actual health and performance. This can lead to perfectly good devices being replaced long before it’s necessary. It also can leave you vulnerable to a device failing before its scheduled replacement or service date.

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Predictive maintenance, on the other hand, compiles data from a device to monitor its performance and applies predictive algorithms to forecast failures long before they happen. More than that, it can help you refine your maintenance schedules and maximize your automation asset investments.

Predictive maintenance is becoming more valuable as more data becomes available — not just from the device itself but from specific components within the device. This is especially true in one of the most important devices in your facility: variable-frequency drives (VFDs).

Deeper Predictive Insights

Whether it’s in a compressor, pump or stamping press, VFDs run the integral processes that keep your production going. If one goes down, your application goes down.

Fortunately, VFDs that are connected via a network now can be accessed, analyzed and tracked over time. What’s more, modern VFDs provide information on some of their core components, such as fans, bus capacitors and insulated gate bipolar transistors (IGBTs).

Fans, for example, are mechanical and eventually will wear out over time. The latest generation of VFDs have prebuilt algorithms that specifically monitor the performance of fans and can predict their life spans accurately based on monitoring temperature, speed of operation and actual hours operated.

A maintenance technician can use this information to repair or replace either the drive or component. And because they can predict failures months in advance, they can plan these services around scheduled downtime events and make sure spare parts are on hand.

Are You Overdue?

If you’re not sure whether predictive maintenance would help your operations, ask yourself:

  • Do you experience regular downtime because of VFD operational performance?
  • Do you schedule regular maintenance to replace components such as VFD fans, filters and IGBTs without knowing whether you’re going to have an issue?
  • Are you using your operational budget instead of your maintenance budget to address drive issues?

If you answered yes to any of these questions, it’s time to consider making VFDs with predictive-maintenance capabilities a priority. You can learn more about VFD options.



The Journal From Rockwell Automation and Our PartnerNetwork™ is published by Putman Media, Inc.


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